Optimization Grid with Random Forest - Not Working.
CarlN
New Altair Community Member
RapidMiner Unicorns 🦄,
I trying to run a optimization grid with our my Random Forest model and I am getting an error. It's stating that gain_ratio criterion cannot be used for numeric labels (see pictures below). I checked all my parameters and I am not using gain_ratio in the optimization grid (see pictures below). So, specifically how you used a optimization grid with cross validation, and random forest predicting a real number in RapidMiner?
Can you send an basic working example of this workflow process with with good documented comments explaining each step.
I trying to run a optimization grid with our my Random Forest model and I am getting an error. It's stating that gain_ratio criterion cannot be used for numeric labels (see pictures below). I checked all my parameters and I am not using gain_ratio in the optimization grid (see pictures below). So, specifically how you used a optimization grid with cross validation, and random forest predicting a real number in RapidMiner?
Can you send an basic working example of this workflow process with with good documented comments explaining each step.
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Answers
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Hi,can you show us your optimization settings? Likely you use least_square there.Also: Be careful using Explain Pred in the X-Val. This can take enormous amount of time.BR,Martin0
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Please see below. Also, I am sending the results of the optimization to a log. Let me know what this issue is or an example workflow process of how this works in RapidMiner.
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Hi,you have a numeric label and try to vary the gain metric between [information_gain,gain_ratio,gini_index,accuracy]. This has to not work, since those are all metrics which don't work on numeric labels.Best,Martin0
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Okay, thanks for the explanation, but the solution is not clear from your response.
Specifically what configuration/setup tasks are needed to make the grid optimization operator work and simply find the optimal parameters for Random Forest model? Do you have a sample workflow of how this can work?0 -
Okay, thanks for the explanation, but the solution is not clear from your response.
Specifically what configuration/setup tasks are needed to make the grid optimization operator work and simply find the optimal parameters for Random Forest model? Do you have a sample workflow of how this can work?
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Hi!
Just select correct and applicable settings for the optimization. Leave the criterion alone (it has to be least_square for numerical prediction) and optimize parameters like the number of trees and the maximum depth.
Regards,
Balázs0 -
I am using least_square in the Random Forest decision tree and it's still giving me an error (see below). I still don't understand why it's not working. Please educate me on the specific, step by step, how-to instructions to make this work. Thank you much.
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